In a Sea of Tech Talent, Companies Can’t Find the Workers They Want
A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.
4 min
There has rarely, if ever, been so much tech talent available in the job market. Yet many tech companies say good help is hard to find.
What gives?
U.S. colleges more than doubled the number of computer-science degrees awarded from 2013 to 2022, according to federal data. Then came round after round of layoffs at Google, Meta, Amazon, and others.
The Bureau of Labor Statistics predicts businesses will employ 6% fewer computer programmers in 2034 than they did last year.
All of this should, in theory, mean there is an ample supply of eager, capable engineers ready for hire.
But in their feverish pursuit of artificial-intelligence supremacy, employers say there aren’t enough people with the most in-demand skills. The few perceived as AI savants can command multimillion-dollar pay packages. On a second tier of AI savvy, workers can rake in close to $1 million a year .
Landing a job is tough for most everyone else.
Frustrated job seekers contend businesses could expand the AI talent pipeline with a little imagination. The argument is companies should accept that relatively few people have AI-specific experience because the technology is so new. They ought to focus on identifying candidates with transferable skills and let those people learn on the job.
Often, though, companies seem to hold out for dream candidates with deep backgrounds in machine learning. Many AI-related roles go unfilled for weeks or months—or get taken off job boards only to be reposted soon after.
Playing a different game
It is difficult to define what makes an AI all-star, but I’m sorry to report that it’s probably not whatever you’re doing.
Maybe you’re learning how to work more efficiently with the aid of ChatGPT and its robotic brethren. Perhaps you’re taking one of those innumerable AI certificate courses.
You might as well be playing pickup basketball at your local YMCA in hopes of being signed by the Los Angeles Lakers. The AI minds that companies truly covet are almost as rare as professional athletes.
“We’re talking about hundreds of people in the world, at the most,” says Cristóbal Valenzuela, chief executive of Runway, which makes AI image and video tools.
He describes it like this: Picture an AI model as a machine with 1,000 dials. The goal is to train the machine to detect patterns and predict outcomes. To do this, you have to feed it reams of data and know which dials to adjust—and by how much.
The universe of people with the right touch is confined to those with uncanny intuition, genius-level smarts or the foresight (possibly luck) to go into AI many years ago, before it was all the rage.
As a venture-backed startup with about 120 employees, Runway doesn’t necessarily vie with Silicon Valley giants for the AI job market’s version of LeBron James. But when I spoke with Valenzuela recently, his company was advertising base salaries of up to $440,000 for an engineering manager and $490,000 for a director of machine learning.
A job listing like one of these might attract 2,000 applicants in a week, Valenzuela says, and there is a decent chance he won’t pick any of them. A lot of people who claim to be AI literate merely produce “workslop”—generic, low-quality material. He spends a lot of time reading academic journals and browsing GitHub portfolios, and recruiting people whose work impresses him.
In addition to an uncommon skill set, companies trying to win in the hypercompetitive AI arena are scouting for commitment bordering on fanaticism .
Daniel Park is seeking three new members for his nine-person startup. He says he will wait a year or longer if that’s what it takes to fill roles with advertised base salaries of up to $500,000.
He’s looking for “prodigies” willing to work seven days a week. Much of the team lives together in a six-bedroom house in San Francisco.
If this sounds like a lonely existence, Park’s team members may be able to solve their own problem. His company, Pickle, aims to develop personalised AI companions akin to Tony Stark’s Jarvis in “Iron Man.”
Overlooked
James Strawn wasn’t an AI early adopter, and the father of two teenagers doesn’t want to sacrifice his personal life for a job. He is beginning to wonder whether there is still a place for people like him in the tech sector.
He was laid off over the summer after 25 years at Adobe , where he was a senior software quality-assurance engineer. Strawn, 55, started as a contractor and recalls his hiring as a leap of faith by the company.
He had been an artist and graphic designer. The managers who interviewed him figured he could use that background to help make Illustrator and other Adobe software more user-friendly.
Looking for work now, he doesn’t see the same willingness by companies to take a chance on someone whose résumé isn’t a perfect match to the job description. He’s had one interview since his layoff.
“I always thought my years of experience at a high-profile company would at least be enough to get me interviews where I could explain how I could contribute,” says Strawn, who is taking foundational AI courses. “It’s just not like that.”
The trouble for people starting out in AI—whether recent grads or job switchers like Strawn—is that companies see them as a dime a dozen.
“There’s this AI arms race, and the fact of the matter is entry-level people aren’t going to help you win it,” says Matt Massucci, CEO of the tech recruiting firm Hirewell. “There’s this concept of the 10x engineer—the one engineer who can do the work of 10. That’s what companies are really leaning into and paying for.”
He adds that companies can automate some low-level engineering tasks, which frees up more money to throw at high-end talent.
It’s a dynamic that creates a few handsomely paid haves and a lot more have-nots.
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A record-breaking $11 million sale at The Centennial Collection has set a new benchmark for luxury apartment living in Bondi Junction.
As interest rates, inflation and market sentiment fluctuate, investors are being urged to focus on data, not panic.
The federal budget has rattled property investors. But the biggest mistake isn’t the tax changes, it’s the conclusion many are drawing from them.
2 min
The recent budget has forced a reckoning for property investors.
Negative gearing now restricted to new residential builds, the CGT discount gone and on paper, the numbers look different.
And many investors are responding by pivoting toward yield, prioritising cash flow over capital growth in a way that property strategists say misses the point entirely.
“The debate has shifted to yield versus growth as if they are opposing forces,” says Abdullah Nouh, founder of Melbourne-based buyers’ agency Mecca Property Group. “But that framing is itself the mistake.”
Nouh, who works with high-net-worth families and investors on long-term acquisition strategy, argues that capital growth remains the primary driver of genuine wealth creation and that the post-budget environment has made quality assets more important, not less.
The numbers make his case plainly. An additional $500 per week in rental income is welcome. A prestige asset appreciating by $1 million over a market cycle is transformative.
These are not equivalent outcomes, and portfolios built around yield at the expense of location and land value tend to generate income while wealth stands largely still.
The more nuanced shift Nouh is seeing among sophisticated investors is a move toward assets where both outcomes can be engineered simultaneously – established homes on substantial land in quality locations, where the existing dwelling can be repositioned, rental returns improved, and the underlying land value compounds independent of what sits on it.
For investors with existing equity, commercial property is also entering the conversation in a more serious way.
Prestige industrial assets, medical centres and long-leased essential retail offer income profiles that residential property in most capital city markets cannot currently match: longer lease terms, tenants covering outgoings, and greater predictability than the residential tenancy cycle.
“The investors who build lasting wealth are rarely the ones who chased yield or growth exclusively,” says Nouh.
“They are the ones who built a strategy they could sustain – one that generated enough income to hold quality assets through multiple cycles while those assets compounded in value.”
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